09:30 Registration opens, coffee/danish
10:00 Gavin Pringle, EPCC, "What is HPC and what EPCC can offer"
10:30 Catherine Inglis, EPCC, "HPC-Europa3: EC funding for research visits using High Performance Computing"
11:30 Chris Johnson, EPCC, "SHAPE: Helping SMEs onto the HPC ladder"
12:00 Stephanie Earp, Optic Earth, "From Academia to Start-up: HPC in Geophysics"
13:30 Lucy MacGregor, Cognitive Geology, "The Impact of Machine Learning in Earth Sciences"
14:00 Mark Howie, Global Surface Intelligence, "The Role of HPC in Deriving Near Real-Time Geospatial Analytics from Satellite Data"
15:00 Mengmeng Zhang, airinnova, "Innovation in Aircraft Design via National and International Collaborative Research using HPC"
15:30 Alberto Marzo, University of Sheffield, "Commercialisation of HPC tools for Personalised Medicine"
Abstracts / slides:
Title: "What is HPC and what EPCC can offer", Speaker: Gavin Pringle - slides available here
Title: "HPC-Europa3: EC funding for research visits using High Performance Computing", Speaker: Catherine Inglis - slides available here
Title: "SHAPE – Helping SMEs onto the HPC ladder", Speaker: Chris Johnson - slides available here
"SHAPE (SME HPC Adoption Programme in Europe)  is a pan-European initiative supported by the PRACE (Partnership for Advanced Computing in Europe) project. Getting SMEs to adopt HPC can be challenging. There are a number of barriers to HPC adoption by SMEs such as a lack of in-house expertise or a lack of available manpower. SMEs may have little or no access to suitable hardware, and an SME may be unwilling to take on the risk of committing to HPC without prior experience. By utilising HPC, an SME has the potential to improve product quality via an enhanced performance and accuracy of their models, or by reducing time to delivery, or by providing innovative new services to their customers. Ultimately this can increase their competitiveness.
The SHAPE programme was set up to help SMEs overcome the barriers they face, allowing them to get a foot on the HPC ladder. Through a series of regular calls, SMEs can apply for assistance from SHAPE via a lightweight application process. Successful applicants to the programme are paired with an expert from a PRACE partner institution who helps them try out their ideas for utilising HPC to enhance their business. In addition SMEs are given access to suitable PRACE supercomputing systems. A typical project could involve the porting or parallelisation of the SME’s code to allow running on an HPC system, getting an SME up and running with a code already installed on an HPC system, or could involve optimising an already running code for the SME’s specific use case .
Since 2013, 45 SMEs across Europe have been awarded effort from the SHAPE programme to assist with making use of HPC for their business. Successful SHAPE projects have come from a diverse range of subject areas, including some less traditional HPC areas such as finance and medicine. This talk will give a short introduction to the SHAPE programme, including some of the success stories from the SMEs across a variety of disciplines that have worked with PRACE."
Title: "From Academia to Start-up: HPC in Geophysics", Speaker: Stephanie Earp - slides available here
"Geophysicists create images of the Earth’s subsurface just like doctors use images to see inside patient’s bodies. This involves collecting large amounts of complex data that need to be processed and sorted to create interpretable images . As well as involving large quantities of data, many of these processes are computationally intensive so a lot of computational power is needed to produce the images in a reasonable time-scale. This talk will show how HPC was used during research in applying machine learning to reduce compute time of imaging in geophysical problems and then discuss the importance of access to HPC resources at the beginning of a start-up."
Title: "The Impact of Machine Learning in Earth Sciences", Speaker: Lucy MacGregor - slides available after research is published
"The oil and gas industry is awash with data, in the form of wells, seismic and other geophysics data, geological information and production data among other things. However, the industry is notoriously poor at utilising this information. The complexity of workflows required to take raw information available in public or proprietary data stores and turn this into decision ready models of sub-surface geology and properties means that such workflows are time consuming. As a result often only a fraction of the available information is used. The resulting sub-surface models are often fraught with uncertainty, and this uncertainty impacts the decision making process for reservoir exploration, appraisal and development. Making better use of information, using modern data analytics techniques, and presenting this information in a way that is immediately useful to geologists and decision makers has the potential to dramatically reduce time to decision and the quality of the decision being made. Here we explore some of machine learning approaches that have been applied to sub-surface interpretation in the past, and look to potential future applications."
Title: "The Role of HPC in Deriving Near Real-Time Geospatial Analytics from Satellite Data", Speaker: Mark Howie - slides available here
"Scotland is well-placed to benefit from the growth in the space industry, particularly the generation of geospatial analytics from satellite data. Whilst GSI (Geographic Information Systems) and remote sensing have been around for a number of decades, the application of machine learning to satellite data is only now becoming practical at large scale. This talk will look at our experience at Global Surface Intelligence, where HPC is the key enabler as we generate near-real time production-level business information for our clients through an automated tool set. Without an effective HPC service we would not be able to offer large-scale products at high resolution."
Title: "Innovation in Aircraft Design via National and International Collaborative Research using HPC", Speaker: Mengmeng Zhang - slides available here
"Zhang is going to talk about the current trend and outcomes in aircraft design within EU research projects involved by Airinnova AB using large-scales and high fidelity simulations with the help of HPC. The aircraft design, especially for novel configurations, requires both fast iteration and acceptable accuracy in the early design stage to save money and time. The high fidelity simulations and Multi-Disciplinary Design and Optimization (MDO), whose aim is to build a "virtual aircraft" which balances all disciplines, are the primary and most advanced tools nowadays used in the aircraft design industry. Airinnova AB will share its experience with a most recent EU project AGILE for aircraft design and MDO, as well as a number of its external and internal projects. All of them were made full use of HPC resources and a significant part of the HPC resources for AGILE and other projects were powered by HPC-Europa3."
Title: "Commercialisation of HPC tools for Personalised Medicine", Speaker: Alberto Marzo - slides available here
"The ‘grand plan’ for in silico  medicine is the creation of a complete mathematical representation of human physiology (a virtual human) that encompasses the entirety of the anatomy, and permits the simulation of any combination of physiological and pathological processes, for the purposes of furthering knowledge, developing healthcare solutions (including treatments), improving clinical practice through stratification and personalised care, and support industry and the regulatory bodies. In full alignment to this ambition, the CompBioMed project is a EU H2020 funded Centre of Excellence focussed on the use, development, and commercialisation of computational methods for biomedical applications. Dr Marzo will give a summary of how the use of HPC has supported the CompBioMed applications along their route to commercialisation, and how Dr Marzo’s research in cardiovascular modelling benefited from HPC-based methods."
 In silico: Activities conducted by means of computer modelling or simulation (alluding to silicon semiconductors).